Bioimpedance presents a versatile, label-free means of monitoring biological cells and their responses to physical, chemical and biological stimuli. Breast cancer is the second most common type of cancer among women in the United States. Although significant progress has been made in diagnosis and treatment of this disease, there is a need for robust, easy-to-use technologies that can be used for the identification and discrimination of critical subtypes of breast cancer in biopsies obtained from patients. This dissertation makes contributions in three major areas towards addressing the goal. First, we developed miniaturized bioimpedance sensors using MEMS and microfluidics technology that have the requisite traits for clinical use including reliability, ease-of-use, low-cost and disposability. Here, we designed and fabricated two types of bioimpedance sensors. One was based on electric cell-substrate impedance sensing (ECIS) to monitor cell adhesion based events and the other was a microfluidic device with integrated microelectrodes to examine the biophysical properties of single cells. Second, we examined a panel of triple negative breast cancer (TNBC) cell lines and a hormone therapy resistant model of breast cancer in order to improve our understanding of the bioimpedance spectra of breast cancer subtypes. Third, we explored strategies to improve the sensitivity of the microelectrodes to bioimpedance measurements from breast cancer cells. We investigated nano-scale coatings on the surface of the electrode and geometrical variations in a branched electrode design to accomplish this. This work demonstrates the promise of bioimpedance technologies in monitoring diseased cells and their responses to pharmaceutical agents, and motivates further research in customization of this technique for use in personalized medicine. / Ph. D.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/63921 |
| Date | 04 November 2015 |
| Creators | Srinivasaraghavan, Vaishnavi |
| Contributors | Electrical and Computer Engineering, Agah, Masoud, Zhu, Yizheng, Lester, Luke F., Strobl, Jeannine Susan, Kelly, Deborah F. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf, application/octet-stream |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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